Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms

1 code implementation • 23 Jul 2019 • Samuel Wiqvist, Andrew Golightly, Ashleigh T. Mclean, Umberto Picchini

Stochastic differential equation mixed-effects models (SDEMEMs) are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dynamics, as well as the variability between experimental units and, optionally, account for measurement error.

Computation Methodology